Titlebook: Algorithmic Aspects of Cloud Computing; First International Ioannis Karydis,Spyros Sioutas,Dimitrios Tsoumakos Conference proceedings 2016

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An Overview of Methods for Handling Evolving Graph Sequencesstance between two vertices through time. Most modern graph processing systems are not suitable for this task since they operate on single very large graphs. In this work we review centralized and distributed methods and solutions proposed towards handling evolving graph sequences.

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0302-9743 in two main tracks: algorithmicaspects of large-scale data stores, and software tools and distributedarchitectures for cloud-based data management..978-3-319-29918-1978-3-319-29919-8Series ISSN 0302-9743 Series E-ISSN 1611-3349

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Density Matrix Theory and Applications In this paper we propose three different approaches for distributed XML filtering using the Hadoop framework. The experimental results clearly demonstrate that the proposed techniques provide good scalability and effectiveness for very large number of document and user queries, compared to traditional XML filtering.

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Distributed XML Filtering Using HADOOP Framework In this paper we propose three different approaches for distributed XML filtering using the Hadoop framework. The experimental results clearly demonstrate that the proposed techniques provide good scalability and effectiveness for very large number of document and user queries, compared to traditional XML filtering.

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男生戴手铐

Conference proceedings 2016l papers were carefully reviewed and selected from 37 initialsubmissions. They cover a wide range of topics in two main tracks: algorithmicaspects of large-scale data stores, and software tools and distributedarchitectures for cloud-based data management..

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Density Matrix Theory and Applicationssome of the dominant platforms, software packages and application delivery tools and architectures that might help a multimedia-related application to be easily deployed, maintained and scale-up with as little limitations to performance and end-user QoE as possible.